Discriminative analysis of Ficus deltoidea Jack varieties using multiplatform metabolomics and development of bioactivity prediction model / Noraini Kasim

Ficus deltoidea Jack (Moraceae) or locally known as ‘mas cotek’ is a popular herb possessing various medicinal attributes. Ethnobotanically, Ficus deltoidea has been claimed to possess antidiabetic properties, the leaf decoction is commonly used as an alternative for type 2 diabetes management. Morp...

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Main Author:	Kasim, Noraini
Format:	Thesis
Language:	English
Published:	2020
Subjects:	Plant biotechnology
Online Access:	https://ir.uitm.edu.my/id/eprint/61110/1/61110.pdf
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spelling	my-uitm-ir.611102022-06-08T02:18:07Z Discriminative analysis of Ficus deltoidea Jack varieties using multiplatform metabolomics and development of bioactivity prediction model / Noraini Kasim 2020-04 Kasim, Noraini Plant biotechnology Ficus deltoidea Jack (Moraceae) or locally known as ‘mas cotek’ is a popular herb possessing various medicinal attributes. Ethnobotanically, Ficus deltoidea has been claimed to possess antidiabetic properties, the leaf decoction is commonly used as an alternative for type 2 diabetes management. Morphology distinction of the seven main varieties (var. angustifolia, var. bilobata, var. deltoidea, var. intermedia, var. kunstleri, var. motleyana and var. trengganuensis) is challenging due to the extreme leaf heterophylly and unclear varietal boundaries. This study aims to establish an analytical method for distinguishing the seven varieties found in Peninsular Malaysia based on comprehensive metabolite analysis. The seven varieties were fingerprinted and profiled using HPLC, MS and NMR. Mass-based dereplication identified 26 compounds comprising of flavanols, proanthocyanidins, hydrocinnamic acids, furanocoumarins and flavone glycosides. In addition, high resolution MS in this work was able to detect new hydrocinnamic acids; 2-O-acetyl-3-O-trans-p-coumaroyltartaric acid and 2-O-acetyl-3-O-cis-p-coumaroyltartaric acid in F. deltoidea with high confidence. Interestingly, var. intermedia was found to contain a unique compound, absent in all other varieties, oxypeucedanin hydrate. Apart for that, generally the varieties contain the same set of metabolites but differ in the quantity. The chemical markers of F. deltoidea, vitexin and isovitexin, were quantified in all varieties using UHPLC analysis. Their content were significantly different across the varieties. Isovitexin content was highest in var. angustifolia with 12.97 μg/g of dry plant material while vitexin content was highest in var. deltoidea with 27.21 μg/g of dry plant material. Multivariate data analysis PLSDA and HCA revealed the existence of three groups based on the differentiation in the metabolite content. Group 1 consists of var. bilobata, group 2 consists of var. intermedia and angustifolia, and group 3 consists of var. motleyana, var. deltoidea, var. kunstleri and var. trengganuensis. Intra-variety analysis of var. trengganuensis from several locations revealed that they are not significantly different. The chemical profiles were quite consistent regardless of nature the plants, cultivated or wild. Even plants growing among bushes on sandy soils and the ones growing on palm trees were similar. At 100 ppm, α-glucosidase inhibitory activity of all collected 112 samples ranges from no inhibition to 71.50%, indicating the varied biological properties. Consequently, PLS predictive model for α-glucosidase inhibitory activity based on the metabolite profiles was constructed. The findings suggest that varieties intermedia (CH), trengganuensis and kunstleri are more superior in terms of α-glucosidase inhibitory activity. Metabolites correlated to α-glucosidase inhibitory activity were identified as 4-aminobutyrate, malic acid, epicatechin, catechin, afzelechin and isoleucine. The validated predictive model was found to be very accurate with the root mean squared error of prediction (RMSEP); 5.4. The correlation model can be useful tool in quality control of F. deltoidea herbal products especially for identification of correct varieties possessing optimal biological properties, eliminating the need for routine bioactivity testing for all samples. 2020-04 Thesis https://ir.uitm.edu.my/id/eprint/61110/ https://ir.uitm.edu.my/id/eprint/61110/1/61110.pdf text en public phd doctoral Universiti Teknologi MARA Faculty of Applied Sciences Ismail, Nor Hadiani (Prof. Dr.)
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Ismail, Nor Hadiani (Prof. Dr.)
topic	Plant biotechnology
spellingShingle	Plant biotechnology Kasim, Noraini Discriminative analysis of Ficus deltoidea Jack varieties using multiplatform metabolomics and development of bioactivity prediction model / Noraini Kasim
description	Ficus deltoidea Jack (Moraceae) or locally known as ‘mas cotek’ is a popular herb possessing various medicinal attributes. Ethnobotanically, Ficus deltoidea has been claimed to possess antidiabetic properties, the leaf decoction is commonly used as an alternative for type 2 diabetes management. Morphology distinction of the seven main varieties (var. angustifolia, var. bilobata, var. deltoidea, var. intermedia, var. kunstleri, var. motleyana and var. trengganuensis) is challenging due to the extreme leaf heterophylly and unclear varietal boundaries. This study aims to establish an analytical method for distinguishing the seven varieties found in Peninsular Malaysia based on comprehensive metabolite analysis. The seven varieties were fingerprinted and profiled using HPLC, MS and NMR. Mass-based dereplication identified 26 compounds comprising of flavanols, proanthocyanidins, hydrocinnamic acids, furanocoumarins and flavone glycosides. In addition, high resolution MS in this work was able to detect new hydrocinnamic acids; 2-O-acetyl-3-O-trans-p-coumaroyltartaric acid and 2-O-acetyl-3-O-cis-p-coumaroyltartaric acid in F. deltoidea with high confidence. Interestingly, var. intermedia was found to contain a unique compound, absent in all other varieties, oxypeucedanin hydrate. Apart for that, generally the varieties contain the same set of metabolites but differ in the quantity. The chemical markers of F. deltoidea, vitexin and isovitexin, were quantified in all varieties using UHPLC analysis. Their content were significantly different across the varieties. Isovitexin content was highest in var. angustifolia with 12.97 μg/g of dry plant material while vitexin content was highest in var. deltoidea with 27.21 μg/g of dry plant material. Multivariate data analysis PLSDA and HCA revealed the existence of three groups based on the differentiation in the metabolite content. Group 1 consists of var. bilobata, group 2 consists of var. intermedia and angustifolia, and group 3 consists of var. motleyana, var. deltoidea, var. kunstleri and var. trengganuensis. Intra-variety analysis of var. trengganuensis from several locations revealed that they are not significantly different. The chemical profiles were quite consistent regardless of nature the plants, cultivated or wild. Even plants growing among bushes on sandy soils and the ones growing on palm trees were similar. At 100 ppm, α-glucosidase inhibitory activity of all collected 112 samples ranges from no inhibition to 71.50%, indicating the varied biological properties. Consequently, PLS predictive model for α-glucosidase inhibitory activity based on the metabolite profiles was constructed. The findings suggest that varieties intermedia (CH), trengganuensis and kunstleri are more superior in terms of α-glucosidase inhibitory activity. Metabolites correlated to α-glucosidase inhibitory activity were identified as 4-aminobutyrate, malic acid, epicatechin, catechin, afzelechin and isoleucine. The validated predictive model was found to be very accurate with the root mean squared error of prediction (RMSEP); 5.4. The correlation model can be useful tool in quality control of F. deltoidea herbal products especially for identification of correct varieties possessing optimal biological properties, eliminating the need for routine bioactivity testing for all samples.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Kasim, Noraini
author_facet	Kasim, Noraini
author_sort	Kasim, Noraini
title	Discriminative analysis of Ficus deltoidea Jack varieties using multiplatform metabolomics and development of bioactivity prediction model / Noraini Kasim
title_short	Discriminative analysis of Ficus deltoidea Jack varieties using multiplatform metabolomics and development of bioactivity prediction model / Noraini Kasim
title_full	Discriminative analysis of Ficus deltoidea Jack varieties using multiplatform metabolomics and development of bioactivity prediction model / Noraini Kasim
title_fullStr	Discriminative analysis of Ficus deltoidea Jack varieties using multiplatform metabolomics and development of bioactivity prediction model / Noraini Kasim
title_full_unstemmed	Discriminative analysis of Ficus deltoidea Jack varieties using multiplatform metabolomics and development of bioactivity prediction model / Noraini Kasim
title_sort	discriminative analysis of ficus deltoidea jack varieties using multiplatform metabolomics and development of bioactivity prediction model / noraini kasim
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Applied Sciences
publishDate	2020
url	https://ir.uitm.edu.my/id/eprint/61110/1/61110.pdf
_version_	1783735214126661632

Discriminative analysis of Ficus deltoidea Jack varieties using multiplatform metabolomics and development of bioactivity prediction model / Noraini Kasim

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